{"as_of":"2026-08-15T06:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:54bd667e3f7c419626ab33088d2e49e0354d441da142bd733cfba5f28389e52a","coverage":[{"denominator":82,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":82,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:47:41.728093Z","state":"measured"},{"denominator":82,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":82,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.23763/citation-record","integrity":"/paper/2505.23763/integrity","json":"/paper/2505.23763/citation-record.json","paper":"/paper/2505.23763"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:33.079072Z","title":"Decore: Deep compression with reinforcement learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:33.079072Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a7e8332374c0a2c812eb8b95f6241cc080aa83b76a3f201d241033152054f3d2","observation_id":"61fb6637-61cf-462b-bd4c-009288a81abf","resolution":{"observed_at":"2026-08-07T12:47:33.079072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:33.226879Z","title":"CLIP for All Things Zero- Shot Sketch-Based Image Retrieval, Fine-Grained or Not","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:33.226879Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:14105178aa4ee158a4d929ba1f4d9ca37b763d3e5a0c52880c6b82a06c837c82","observation_id":"4c9004ef-7640-41f7-abe0-1c75fcb7fdcd","resolution":{"observed_at":"2026-08-07T12:47:33.226879Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:54.759009Z","title":"Do deep nets really need to be deep? NeurIPS, 2014","venue":null,"work_id":"b5dc3584-1af1-4588-9dc7-fec85e566892","year":2014},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:33.435442Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:db9e6fa1ef7bec33ac053c531b2b6867384f60d305b0c10198d4d1668638eb5c","observation_id":"f4d9913a-473d-4bda-a11e-2f0f85c55e2a","resolution":{"observed_at":"2026-08-07T12:47:54.840283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.02641","last_updated":"2018-05-07T17:52:42Z","snapshot_observed_at":"2026-08-14T19:17:57.386021Z","submitted_at":"2018-05-07T17:52:42Z","title":"Label Refinery: Improving ImageNet Classification through Label Progression","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.02641","snapshot_observed_at":"2026-08-07T12:47:33.553089Z","title":"Label refinery: Improving ima- genet classification through label progression.arXiv preprint arXiv:1805.02641, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:33.553089Z"},"links":{"cited_paper":"/paper/1805.02641","citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d332770c321b3631a6b90adfe1e6ee5331bc791016beed6c2a179619f1a8fea2","observation_id":"76af6a9e-953c-4f67-8edd-abe52e4dc7aa","resolution":{"observed_at":"2026-08-07T12:47:33.553089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:54.579990Z","title":"Pixelor: A competitive sketching ai agent","venue":null,"work_id":"2eeda8f5-d77e-4726-92a4-3793c544ed07","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:33.709386Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:8631ab166056b6cbc5f6ae9b0ad463f017599b77181c88363f08768e12485e17","observation_id":"90a79be0-e9c9-4444-9499-77402fb6c057","resolution":{"observed_at":"2026-08-07T12:47:54.672435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:54.396359Z","title":"Sketch less for more: On-the-fly fine-grained sketch based image retrieval","venue":null,"work_id":"4b2fe170-e636-47a6-9a2d-2aff04a12121","year":2020},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:33.918529Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c3c982d88f0377dc876f913a53855de5597edfce21d99d2cfe1962b36703da4a","observation_id":"6b8f934b-8f9c-4c2d-959c-8d7cf1d18f75","resolution":{"observed_at":"2026-08-07T12:47:54.455503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:54.237521Z","title":"More photos are all you need: Semi-supervised learning for fine- grained sketch based image retrieval","venue":null,"work_id":"3aa6df47-b957-45cf-961c-b6525346f47d","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.037159Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a9456f71baf4d38a2142c9a86b459577f7da439ce791de66d1d933ee65cf2417","observation_id":"39fb5aeb-71e5-49e1-8fcc-bf238d5dffd0","resolution":{"observed_at":"2026-08-07T12:47:54.310066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:54.082245Z","title":"Vectorization and rasterization: Self-supervised learning for sketch and handwriting","venue":null,"work_id":"48842586-7d20-4ab5-ad84-e603dd45cfe3","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.158767Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:4123c47bddad50c435d857c2ef83e75b20b922a45816db4e86d5355d7c4f2541","observation_id":"9bb2f67f-ceb0-4a59-b1af-5d8379bd2be5","resolution":{"observed_at":"2026-08-07T12:47:54.139064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:53.899722Z","title":"Sketching without worrying: Noise-tolerant sketch-based image retrieval","venue":null,"work_id":"f29378fb-8ac6-413e-ab18-3900ca8c2d2d","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.253155Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:790e9e3c9fd6dd7e80eff0f34640083ab460eeec47d2a8d5310767e281827c6f","observation_id":"8621d240-59d4-4e18-b3b6-9e03e80422d2","resolution":{"observed_at":"2026-08-07T12:47:53.959987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:53.687552Z","title":"Sketch2Saliency: Learning to Detect Salient Ob- jects from Human Drawings","venue":null,"work_id":"7c927781-70b5-43dd-94f7-00771e9a7486","year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.329242Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:521662473aa472ecac94e9341003d4bec90a133c6b93c3f37b17b00072df5318","observation_id":"742eeabd-220f-4d56-90c5-a44a89c2ca8e","resolution":{"observed_at":"2026-08-07T12:47:53.795655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:34.394943Z","title":"A simple framework for contrastive learning of visual representations","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.394943Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:e3cfa53b0a56910dfda170058bbb8af0c980d6f51ea1b1aacc6e7cefcd160bd0","observation_id":"fab17c71-d44c-4d56-beb6-4bf45e0f8554","resolution":{"observed_at":"2026-08-07T12:47:34.394943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:53.400264Z","title":"Mobile- former: Bridging mobilenet and transformer","venue":null,"work_id":"4bbb66a4-eb56-4b33-9b1a-4d30f692c3ba","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.502698Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:1856995fbebc9689704e1e812bd075344a7ba97a53efaaaeb10a661053acc80b","observation_id":"e681c662-aca8-4d5e-a476-8931a705ab9a","resolution":{"observed_at":"2026-08-07T12:47:53.482088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:53.240336Z","title":"Dynamic low-resolution distillation for cost- efficient end-to-end text spotting","venue":null,"work_id":"e598f67e-bd19-450e-9fb1-81133ed0bbc4","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.631751Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:3b358bec370a30c636fd2ef098e32adacf4d16d9d713b5d6979c087291b6a2a7","observation_id":"ec041dfe-bdae-485b-8acc-ab96045fcb1c","resolution":{"observed_at":"2026-08-07T12:47:53.296238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:53.105444Z","title":"Partially does it: Towards scene-level fg-sbir with partial input","venue":null,"work_id":"5586d917-61c7-4ed6-9a4c-27cf544db124","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.703170Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:80cb7003b02782de6173def037a2d06a57632770e9db713d72817d12cd313e33","observation_id":"4e70c51e-f54d-4b43-a772-3c36e5cf5fae","resolution":{"observed_at":"2026-08-07T12:47:53.160570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.990263Z","title":"Partially does it: Towards scene-level fg-sbir with partial input","venue":null,"work_id":"d3bd896f-ecd0-4738-a0d0-1873a3cbf46d","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.813587Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:593af89428be61a5724b038d30c21d903dcdfc60914b63601e9cfeb1ea1cc30d","observation_id":"fa61f5f5-c71c-4dbe-97a5-af7bcacf6adf","resolution":{"observed_at":"2026-08-07T12:47:53.030620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.845856Z","title":"Fs- coco: Towards understanding of freehand sketches of com- mon objects in context","venue":null,"work_id":"d648e1be-7c81-438d-b4a2-5e9cdfdfb1a8","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:34.923892Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:12aef7d5cfcca43b7b06ed11e93c1241c8de3a3b81953b02cb1f68c85e79c9c4","observation_id":"cc5c9c71-b36f-42f9-9785-3e659f4e8d92","resolution":{"observed_at":"2026-08-07T12:47:52.902561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.720281Z","title":"Democratising 2D Sketch to 3D Shape Retrieval Through Pivoting","venue":null,"work_id":"6351a4e7-cacd-43c9-93f2-a6c87ed1e0ed","year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.014084Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:cce7e92a1b1819c489a478860222f4b144090abd55e48a98a64d53b2370b4d73","observation_id":"f5b4c76e-36fb-457a-8eb2-7d0fa95232f1","resolution":{"observed_at":"2026-08-07T12:47:52.766605Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.519011Z","title":"Livesketch: Query perturbations for guided sketch-based visual search","venue":null,"work_id":"85927dc5-d569-475e-a851-f45b11ecb83f","year":2019},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.089842Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d516760d6f754eec1912221a958194caf10c0c41e46cc35b5d4e7c5bb0819018","observation_id":"d6985629-fce6-4f50-954d-1c17f8b82176","resolution":{"observed_at":"2026-08-07T12:47:52.613671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.403071Z","title":"Binaryconnect: Training deep neural networks with binary weights during propagations","venue":null,"work_id":"72ee201c-5de9-4288-a067-8933a7df8121","year":2015},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.199728Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:260f8422a220383e3b9259b855737ed4a6e9e1295afd2a610d9579d139f768c2","observation_id":"f014ee93-1d7c-4d91-8209-41f9b1dc86cc","resolution":{"observed_at":"2026-08-07T12:47:52.457617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.257362Z","title":"Doodle to search: Practical zero-shot sketch- based image retrieval","venue":null,"work_id":"c66f2376-7fc1-445f-be50-8bd44abdf6d5","year":2019},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.310326Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:00338a1663505690940c3647b9700fea50f5450d8db4a777b3fa50c3c082a029","observation_id":"fb4bcd3c-5385-4e77-9188-a64356413720","resolution":{"observed_at":"2026-08-07T12:47:52.325920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:52.132218Z","title":"Semantically tied paired cycle consistency for zero-shot sketch-based image retrieval","venue":null,"work_id":"02025860-ab34-4bae-9d65-2cac2506a797","year":2019},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.404022Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:8fb3fb70678a478baa103db9e7244968432f869c52e37acb160e79537f46fc96","observation_id":"9198f97f-48d2-4bf6-9054-118328707f68","resolution":{"observed_at":"2026-08-07T12:47:52.186251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:51.963041Z","title":"Deep learning with limited numerical precision","venue":null,"work_id":"7f1e7b63-7e99-4212-84fa-d33a9461eba4","year":2015},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.544939Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a14781c168efec384406b89b164573bc663f40479bb7527ef17bb608c4ae9120","observation_id":"dc659151-8c90-4f80-a7f2-89897c43351d","resolution":{"observed_at":"2026-08-07T12:47:52.064097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:51.704577Z","title":"A neural representation of sketch drawings","venue":null,"work_id":"87e2f2b4-d144-414e-a8de-66b83abda9ac","year":2018},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.635045Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:130601ac7f9301e6c5bae7bb64f7db9ae4e3ace30e17f8dac5b25e0097697d1c","observation_id":"7700f746-065f-4d49-9187-216f99268031","resolution":{"observed_at":"2026-08-07T12:47:51.824084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:51.457321Z","title":"Deep com- pression: Compressing deep neural networks with pruning, trained quantization and huffman coding","venue":null,"work_id":"fb4b98b3-1418-4a9a-8a82-6a5d48896970","year":2016},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.708152Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:7316500ff00c1f8b7dd1e658a26a1ddbb75833233c7e00ba8fcaaf86a4263b10","observation_id":"86a6607c-6219-46f7-b9f7-cbcbaf5359e8","resolution":{"observed_at":"2026-08-07T12:47:51.587609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:35.794012Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.794012Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:2eca337872608f5aedd9f06665fa2c7cb3d1d5fa7e3aa86449ab54c0077867c5","observation_id":"df468551-6424-47aa-bae1-cbb4375d6fb3","resolution":{"observed_at":"2026-08-07T12:47:35.794012Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:51.212531Z","title":"Distilling the knowledge in a neural network","venue":null,"work_id":"86ba629f-203c-43ac-996f-1ccbcd3ee483","year":2014},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:35.921155Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:384dd6b834ea5b155ca6b4060d36fe1562e9fc4869d5eee30c484e5b10dd153d","observation_id":"3ea24f2f-e20e-4d99-b53c-f9a984b3f8fa","resolution":{"observed_at":"2026-08-07T12:47:51.306637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:51.093226Z","title":"Densely connected convolutional net- works","venue":null,"work_id":"7f7a1912-3805-42db-a0e0-f6994af2f021","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.013889Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c0b995857d4fa3eda511d4340e11248bd4db8050719029596a3a15f091f52ef8","observation_id":"27f459e1-b4f6-4cf3-8390-f85827148d57","resolution":{"observed_at":"2026-08-07T12:47:51.135112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:51.008278Z","title":"Robust pairwise learning with huber loss","venue":null,"work_id":"eb99e595-f176-4652-8c2d-8323dbadb51f","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.110540Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:72bb48403451433836fe7a574f8408ac0b1731c0b3f7c63776181f36e774dc57","observation_id":"da58db63-ab38-4892-9a1b-9fdbae3c25a4","resolution":{"observed_at":"2026-08-07T12:47:51.040102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.01219","last_updated":"2017-12-18T22:35:22Z","snapshot_observed_at":"2026-08-14T20:49:40.190420Z","submitted_at":"2017-07-05T05:44:02Z","title":"Like What You Like: Knowledge Distill via Neuron Selectivity Transfer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.01219","snapshot_observed_at":"2026-08-07T12:47:36.226690Z","title":"Like what you like: Knowl- edge distill via neuron selectivity transfer","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.226690Z"},"links":{"cited_paper":"/paper/1707.01219","citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:42616b5fab623687ff43255441d10afc4a2d263370badced3cd7881d8cf38f2b","observation_id":"7cb47b7d-bd18-4e77-9f1d-ca5111e73b38","resolution":{"observed_at":"2026-08-07T12:47:36.226690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.913973Z","title":"Reinforcement learning: A survey","venue":null,"work_id":"3aaaa861-4879-456f-94db-1bb41f9763ab","year":1996},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.337461Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:9b640b602cb885f4fb59b685eda2766cc2d56acd8d6b2a1d6f34e6b342a32204","observation_id":"2fff80e5-8723-47e0-a398-649f57418f24","resolution":{"observed_at":"2026-08-07T12:47:50.952518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.853606Z","title":"Very deep convolu- tional networks for large-scale image recognition","venue":null,"work_id":"9e66c928-842e-423d-869e-5582aeffa34e","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.421798Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:17b0a7b61141e18bcca4c6cd973f6243895daa50d31110770f0650f7960a5825","observation_id":"051de0fa-a789-4c41-93c9-aa5b1a1702d2","resolution":{"observed_at":"2026-08-07T12:47:50.880370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.706563Z","title":"How to handle sketch-abstraction in sketch-based image retrieval? In CVPR, 2024","venue":null,"work_id":"14e91721-4cb4-41c9-abf8-ee39c7f7da63","year":2024},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.549794Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:37312ed927ad9a1649606f4d242b689f07d53be8c669ea55befcf05e29b2fdcb","observation_id":"19ea2182-12d0-405d-975d-886b3a0b8804","resolution":{"observed_at":"2026-08-07T12:47:50.772623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.579479Z","title":"A2- rl: Aesthetics aware reinforcement learning for image crop- ping","venue":null,"work_id":"106b8ae2-3a7c-45ff-ab48-bf487ea729d8","year":2018},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.656116Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:9047acd94bd014685eaf9872a5784ac8406ce90285705a4c7185ff11f8ee068d","observation_id":"9271e531-cfd3-4d16-9ce9-efae684cdd7b","resolution":{"observed_at":"2026-08-07T12:47:50.638409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.381400Z","title":"Learning to learn cropping models for different aspect ratio require- ments","venue":null,"work_id":"cc2175b5-7b5f-49f6-bb81-3acc8c530348","year":2020},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.721396Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:1f8bac4494868576507d24f6125c07603fd4b8ac01c12e1c34e23f35a0d6b4bb","observation_id":"4fe6f9fb-bb76-422e-8427-fb600753985e","resolution":{"observed_at":"2026-08-07T12:47:50.473830Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.187864Z","title":"Deep variation- structured reinforcement learning for visual relationship and attribute detection","venue":null,"work_id":"b2fa2aa1-affb-4ae8-a889-a4c9b4a32779","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.808429Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a06c290ed0e9a71a23edeb9fa5ff3e24476f64e6956806ef865abfa095f4dc41","observation_id":"ceff2a71-2f29-4abe-bfff-29ac2aa4f3e5","resolution":{"observed_at":"2026-08-07T12:47:50.244582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.086663Z","title":"Fixed point quantization of deep convolutional networks","venue":null,"work_id":"a68f1549-3216-43ed-a657-40c575ebfa05","year":2016},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:36.952855Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c29a9e036b401e67d62697ae345d4c35459e7386794c8424f3a4556a1aff2f71","observation_id":"2750f8d2-77e2-4f3d-a3a1-6e779247b420","resolution":{"observed_at":"2026-08-07T12:47:50.124079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:50.007223Z","title":"Sketch-bert: Learning sketch bidirectional encoder rep- resentation from transformers by self-supervised learning of sketch gestalt","venue":null,"work_id":"a078fc12-fb04-4c85-a6b7-8539c1074ab5","year":2020},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.017383Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a44a7160c24e732db1d165344f73f7a3e5096d8b7461c91d7f2cfc7252af4f4a","observation_id":"97d755e6-bfc0-40b0-a4f6-a0de8c78529c","resolution":{"observed_at":"2026-08-07T12:47:50.033417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:49.762152Z","title":"Deep sketch hashing: Fast free-hand sketch-based im- age retrieval","venue":null,"work_id":"65fc0dee-76e5-4be1-a91b-b0a2a7d43121","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.097151Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:413565a5409cce4c16895b111c087aea5a93c6357fd7a6a2528597eaed30177d","observation_id":"97bee932-8fbd-4950-ac67-2671a98b71ad","resolution":{"observed_at":"2026-08-07T12:47:49.906358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:37.184755Z","title":"Efficientvit: Memory efficient vision transformer with cascaded group attention","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.184755Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:5903d9943370835c683916e2f07269d02d854eac14df1660ad55a7d6e27f6836","observation_id":"55d4e1f0-ced0-49f1-9995-0b81e6ff3281","resolution":{"observed_at":"2026-08-07T12:47:37.184755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:49.320725Z","title":"Thinet: A filter level pruning method for deep neural network compression","venue":null,"work_id":"b9fd7d7d-4a69-4576-8ec4-37c02a7e4e38","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.306876Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:acdb4742554ba78d492db4fb2b7dcca6ca6d71d6b2b1da347416150d2d8bea9c","observation_id":"12f27330-d47c-4fb6-b9a4-4366938a7516","resolution":{"observed_at":"2026-08-07T12:47:49.471567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1611.06440","last_updated":"2017-06-08T19:53:26Z","snapshot_observed_at":"2026-08-14T21:29:36.502364Z","submitted_at":"2016-11-19T22:48:30Z","title":"Pruning Convolutional Neural Networks for Resource Efficient Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.06440","snapshot_observed_at":"2026-08-07T12:47:37.451402Z","title":"Pruning convolutional neural networks for re- source efficient inference","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.451402Z"},"links":{"cited_paper":"/paper/1611.06440","citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:58f7880020fdf74291684208bba991401dfac738be2e1cce27a44486da043165","observation_id":"d9191e68-8b76-4e9b-b0a5-b59256da496e","resolution":{"observed_at":"2026-08-07T12:47:37.451402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:48.906343Z","title":"Learning deep sketch abstraction","venue":null,"work_id":"7e3c22b0-eee2-48c4-9434-7a57d5ce327a","year":2018},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.563086Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:10b41bb9fad5ecb64f82358735b18459c8ae04ecb3f1d8a9fe34bb3130767786","observation_id":"6cc955f0-496d-4959-8dfe-98c25ec895d8","resolution":{"observed_at":"2026-08-07T12:47:49.125740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:48.603493Z","title":"Goal-driven sequential data abstraction","venue":null,"work_id":"e40da42d-c611-497b-9f87-3f2d2d5f0fd5","year":2019},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.663951Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c2c5a8dd8f739aa3885c756cc9c4787faf730b3f5fc9f332ea6bfcd7f499154f","observation_id":"cff6824a-a000-4039-b9c7-9bfabfbc8ab1","resolution":{"observed_at":"2026-08-07T12:47:48.656674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-11T10:12:11.384939Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-07T12:47:37.748199Z","title":"DINOv2: Learning Robust Visual Features without Supervi- sion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.748199Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:1361fb00304936f1a5497991e54c050ffb90b9990a085dd5e532b1fc102d19f4","observation_id":"1bdc30ef-e34e-4c3f-8597-07a4ba0799bc","resolution":{"observed_at":"2026-08-07T12:47:37.748199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:48.362807Z","title":"Cross-domain generative learning for fine- grained sketch-based image retrieval","venue":null,"work_id":"e22445d1-e41b-4805-b98f-06e15c2c3d6b","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:37.884853Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:17cbda0df5f79bfbf06440ae6b2ed981af25ef91867ce167697e229e9e128fa7","observation_id":"7f436804-ddb8-44bc-983f-3619e43146c5","resolution":{"observed_at":"2026-08-07T12:47:48.460738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:48.197829Z","title":"Gener- alising fine-grained sketch-based image retrieval","venue":null,"work_id":"beb81d26-088e-4ac6-90ee-d17adf5acd1a","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.008513Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:ca0b892f20395919391be56aca7b5aa08d32c587d4ca142bdebe59a470e933b5","observation_id":"cdd7fc32-c0ee-48ee-93bd-fb076e7387d4","resolution":{"observed_at":"2026-08-07T12:47:48.280017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:48.023010Z","title":"Solving mixed-modal jigsaw puz- zle for fine-grained sketch-based image retrieval","venue":null,"work_id":"20e5201e-af8f-4447-93d9-d9ceb02db617","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.108570Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c77483b213b7417f8c8af6f2366c186f00b681f3e9e32ad390b35d7b1de3e776","observation_id":"d71f6598-cd88-4fb5-ac37-9715585cacdf","resolution":{"observed_at":"2026-08-07T12:47:48.106815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:47.862738Z","title":"Learning deep rep- resentations with probabilistic knowledge transfer","venue":null,"work_id":"4be8ee91-de03-4ed8-9158-8376051ca87c","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.188767Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:800b328c094d6650d6e656e0c3b73a8fef71a228996607b360b7f2e08c333d49","observation_id":"08ba70da-8e81-403d-8fed-7adfe3aff56f","resolution":{"observed_at":"2026-08-07T12:47:47.913696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:47.660510Z","title":"SceneTrilogy: On Human Scene-Sketch and its Com- plementarity with Photo and Text","venue":null,"work_id":"f73558d2-3448-42df-b8ff-326604e94dcc","year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.280092Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d5839547349f714df06f87170a986690c5b393b0885ee80f1fba56c3de5d38c0","observation_id":"d2cae4b8-17d3-418d-a578-b112d18deac0","resolution":{"observed_at":"2026-08-07T12:47:47.741721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:47.464538Z","title":"What Can Human Sketches Do for Object Detection? In CVPR, 2023","venue":null,"work_id":"ee0a8ee5-987b-4f8b-94cd-950585e1b5b2","year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.391741Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:ce00533b695bb02c543719ef330360457ac02e1a6941c0789b007833897ea476","observation_id":"9485163a-31ad-4cc4-a854-b0171d99476c","resolution":{"observed_at":"2026-08-07T12:47:47.543021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:47.148155Z","title":"Fitnets: Hints for thin deep nets","venue":null,"work_id":"8e3a409c-1491-4c26-bd00-6ce57f217057","year":2015},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.472405Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:59313aadc189c5c8dc4036ddc16b63fad244d0961caea91b8266f246b554537c","observation_id":"a5d9c73f-cce8-429d-b730-353fac4b59cd","resolution":{"observed_at":"2026-08-07T12:47:47.333326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:46.773166Z","title":"Imagenet large scale visual recognition challenge","venue":null,"work_id":"df06a73c-ebdb-4a2b-b6ba-6ce6cf2c8593","year":2015},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.560332Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:498350a3b778246dd0bc6d863221a548e67bbe9f83f02a2aeccab0586dd66f97","observation_id":"de9a4849-1284-4bb4-be41-5b3b9d239197","resolution":{"observed_at":"2026-08-07T12:47:46.944250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:46.562501Z","title":"Cross-modal hierarchical modelling forfine-grained sketch based image retrieval","venue":null,"work_id":"8080a9c0-9fd0-431c-a57b-b5ad261b1040","year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.670546Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:b8201abfdf8137b392aeaaed7c2feefe73f9c4bb14acaac088aca95520ceac43","observation_id":"3d9663d9-fb87-4fd6-b679-1898977ace31","resolution":{"observed_at":"2026-08-07T12:47:46.640462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:46.416306Z","title":"Stylemeup: Towards style-agnostic sketch-based image retrieval","venue":null,"work_id":"51381e7a-589c-45e6-b31e-527c95170da3","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.771756Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c19f9c1cbf3f678cd323e9517219b8c1275b4b4fc1a821539f26df2d345a3dc7","observation_id":"918b04da-ee13-4b3b-81ba-a0111b61f702","resolution":{"observed_at":"2026-08-07T12:47:46.455554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:38.862481Z","title":"Sketch3t: Test-time training for zero-shot sbir","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.862481Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:60c5e736a8b7f0ce21d11ba16bb95bb05711b75fe8d566478cb205f1a6fd7e72","observation_id":"a03df94d-f60d-4014-aa57-5518a118b87b","resolution":{"observed_at":"2026-08-07T12:47:38.862481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:46.223826Z","title":"Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR","venue":null,"work_id":"94475869-b753-4f01-b935-67614d3f3bce","year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:38.984570Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:177427d5aead5f567b6adee2d32da0104211593a8d3c85da4aa71a247e1072bd","observation_id":"8c4cd0f6-cb69-4dcd-88a2-acc3e8c22149","resolution":{"observed_at":"2026-08-07T12:47:46.288869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:46.033257Z","title":"Mobilenetv2: Inverted residuals and linear bottlenecks","venue":null,"work_id":"add976dd-b29e-430c-9c0d-b62eb9804673","year":2018},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.060477Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:4b47363a944e9cc3b69cd99eec70c38cab52c81a00ec8551e3735dd5608655db","observation_id":"dbd1bdc1-4e74-498d-8b1d-4e9728902654","resolution":{"observed_at":"2026-08-07T12:47:46.100444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:45.866546Z","title":"The sketchy database: learning to retrieve badly drawn bunnies","venue":null,"work_id":"e3994442-2ea6-4630-b775-8a0e180ecd10","year":2016},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.171999Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a7babe9b1da9e9fac74505f9ee6133f2ab5c36f03cbb956320f5e1e84dd0d21a","observation_id":"6e280076-b58b-4225-84fa-92b88f420af0","resolution":{"observed_at":"2026-08-07T12:47:45.968411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-07T12:47:39.247458Z","title":"Proximal policy optimization algo- rithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.247458Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:5120b77c39086b21bab2e20db0d9c2119700e75d96e985776e9ef6d2fb5d41ef","observation_id":"9b73a145-cdf3-4f61-9702-dfa9f1ebb259","resolution":{"observed_at":"2026-08-07T12:47:39.247458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:39.349998Z","title":"Very deep convo- lutional networks for large-scale image recognition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.349998Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:fb64cc21f1c961c65c37beaa3483b0fb424f6bce76c4beb39a0db4df55420ced","observation_id":"5acbe9c2-e187-4b53-b573-52010add8695","resolution":{"observed_at":"2026-08-07T12:47:39.349998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:45.659691Z","title":"Fine-grained image retrieval: the text/sketch input dilemma","venue":null,"work_id":"54c24ef4-dbf0-4e55-aaa4-7e6609ca9024","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.489208Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:8986f709ddac7486f61692a54d58d710da44aa2cf3aa9280351ed237ee0857b6","observation_id":"667f0e29-72d1-4e1d-a149-d7c4121ead21","resolution":{"observed_at":"2026-08-07T12:47:45.728377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:45.523394Z","title":"Deep spatial-semantic attention for fine- grained sketch-based image retrieval","venue":null,"work_id":"2deff41b-09cf-4365-b387-2fcf5ea2c839","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.598041Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:68b6ce41fe1322b85e3ae4f22e42d27aed3865cf4fb72e3d8e79a25d3cdf86e7","observation_id":"827a29eb-3b4c-4fd9-8b72-c260aff8fa63","resolution":{"observed_at":"2026-08-07T12:47:45.591073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:45.363870Z","title":"Picture that Sketch: Photorealistic Image Generation from Abstract Sketches","venue":null,"work_id":"63fe5617-c5cd-41d5-9b18-0de4b43c780a","year":2023},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.711097Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:66f13bd2af301cf1954ab3824f322a8c5eea649e4ab97270a0cac0a151a45466","observation_id":"767cab3c-02e7-451e-85b2-fe482153bd29","resolution":{"observed_at":"2026-08-07T12:47:45.424649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:45.218538Z","title":"Policy gradient methods for reinforcement learning with function approximation","venue":null,"work_id":"31d567e3-45c3-4f38-bdf9-226f0ae465e9","year":2000},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.814691Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:7d91f89fb7eca6e78662b4459e5eb033bfb134924180fc04270003c3ad2ee1e2","observation_id":"23702eb3-e26a-406d-b5c7-08023800e394","resolution":{"observed_at":"2026-08-07T12:47:45.275894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:45.074371Z","title":"Learning to resize im- ages for computer vision tasks","venue":null,"work_id":"80028cd8-fbce-4bcf-a57d-dd56d100258b","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:39.912788Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:a1cb77e3d7e0424fa654f8a9d671979441667e1852b3d5165fce8601252626e7","observation_id":"0b7cd4fb-8c90-4445-8723-ae7921654d93","resolution":{"observed_at":"2026-08-07T12:47:45.132747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:44.921655Z","title":"Efficientnet: Rethinking model scaling for convolutional neural networks","venue":null,"work_id":"b3dc98b9-d700-4c09-8250-2e003061abb9","year":2019},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.057696Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:65d58582ddadf8d7ad3bab20c97a321f0efe76e1d09055e3cd14ab782985e1f4","observation_id":"c1de1c4c-8b20-4d99-814d-2d2326c43f63","resolution":{"observed_at":"2026-08-07T12:47:44.983836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:44.753956Z","title":"Learning when and where to zoom with deep reinforcement learning","venue":null,"work_id":"d9d48e0a-9ef6-4596-a3c3-bf31029e0f94","year":2020},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.159680Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:ca32bb80394fc42ec36042a0c70268d933f54f7c7aa80c4759db080e5143f61b","observation_id":"f39b0405-23c9-464f-ad9f-b3b202952a2e","resolution":{"observed_at":"2026-08-07T12:47:44.827038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:44.585449Z","title":"White blood cell classification: a comparison be- tween vgg-16 and resnet-50 models","venue":null,"work_id":"9d92dcfd-4b20-480b-bfdb-154b8f3a9978","year":2018},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.236405Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d00981f13d5b2efeaf41d4547c5c6c0aeb4eb886d9026599b831ddbc52c36c55","observation_id":"919fbb04-6b7c-481e-8bd8-d18b49493951","resolution":{"observed_at":"2026-08-07T12:47:44.648514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:44.394382Z","title":"The douglas- peucker algorithm for line simplification: re-evaluation through visualization","venue":null,"work_id":"fa27edd0-90d9-4068-9ec7-2060d401dd8b","year":1990},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.347023Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:55bc09fdd195f9437cbf54fe9c63908b9861618243ef0090b9e2a2d6b10c6efa","observation_id":"d288b66c-5ffe-428c-8c57-002e3570e9c3","resolution":{"observed_at":"2026-08-07T12:47:44.472519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:44.207003Z","title":"Deep reinforced attention regression for partial sketch based image retrieval","venue":null,"work_id":"cba70f3f-5a4e-417b-beaa-04100ba2a660","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.474509Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:759e820df70f9e35f4b5c161966ef340bb20db9bc38b6219ed6faea1ac028d4c","observation_id":"a7cc7f95-9e2f-4529-a1d2-c47bc3a7107b","resolution":{"observed_at":"2026-08-07T12:47:44.293892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:44.019006Z","title":"Reinforced cross-modal matching and self- supervised imitation learning for vision-language navigation","venue":null,"work_id":"adc4eedf-2738-4c0b-bbd9-4ef90e229403","year":2019},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.561984Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:b18d390aff0e928f3b211c1c51187898708822d1a00565d25be3e78817c9a1c2","observation_id":"d73c68b2-94c8-4288-8340-74e978778b89","resolution":{"observed_at":"2026-08-07T12:47:44.096401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:43.872677Z","title":"Cnnpack: Packing convolutional neural networks in the frequency domain","venue":null,"work_id":"379af7c3-2a0c-44aa-ae2d-e136aa17902b","year":2016},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.690009Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:c35b7d853327f78bfbc15a7242febe332498d4e3204093c3a969b3c4b0cce3f2","observation_id":"23358ca9-ca09-4dff-8550-6bdfde98bb1c","resolution":{"observed_at":"2026-08-07T12:47:43.936195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:43.671091Z","title":"Glance and focus: a dynamic approach to reducing spatial redundancy in image classification","venue":null,"work_id":"ebb92d6a-aa97-49ca-ae4d-ab1c24727a6b","year":2020},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.801952Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:ba725f6130f94c7e26aabe84218962fa1a31e9aa1fce008c3ae4bd26b707ce25","observation_id":"93e31d9c-4b2f-4226-95f7-088b19ae2a66","resolution":{"observed_at":"2026-08-07T12:47:43.770629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:43.482674Z","title":"Distance met- ric learning for large margin nearest neighbor classification","venue":null,"work_id":"95acdd97-0f99-4a80-bf78-41104d676b66","year":2009},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.892031Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d70b0dbcd6b0128dc6122cdf51803ddd1d2aed66e950127051b51ca94617f9ed","observation_id":"1accfcdc-a840-4c61-b0e1-ba9abc3c707d","resolution":{"observed_at":"2026-08-07T12:47:43.557383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:43.277352Z","title":"Multi- graph transformer for free-hand sketch recognition","venue":null,"work_id":"624c952c-cbb0-4e96-bfe8-71841627636c","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:40.983710Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:524449c1273ba2613f88d2bfa689ce3100c999bf05aed409b707b8ff846170f2","observation_id":"4592ea39-bcde-4fdc-8f80-f600e1a1c112","resolution":{"observed_at":"2026-08-07T12:47:43.364218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:43.091013Z","title":"Deep learning for free-hand sketch: A survey","venue":null,"work_id":"3f1ea4bf-01fd-4ca1-89a3-cd01d891198c","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.095734Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:04e86f0f06c5006d5564b3ecf696cb010d90e8032de9b81b3ad60bbda6023d50","observation_id":"d3964cdd-6147-4884-ad80-c560f0b6c7ce","resolution":{"observed_at":"2026-08-07T12:47:43.142537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:42.891034Z","title":"SmartAdapt: Multi-branch object detection framework for videos on mo- biles","venue":null,"work_id":"8b1d9c71-1576-4dc0-8306-430bbf619c7b","year":2022},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.202566Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d98965812f43ac5c5a45feef856dee3fd7d2d4e4f1ec277d55cdae5b8bb9d737","observation_id":"5cefbf80-e243-4c08-a1f3-a4ef64ec2a57","resolution":{"observed_at":"2026-08-07T12:47:42.977811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:42.732403Z","title":"Hospedales","venue":null,"work_id":"bc0e5731-bbf1-47b5-9077-54b510b10313","year":2015},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.303675Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:cd919650ff7d89a3c0c5f10a0532b19aad48a3bd98106df4b7a4fed2823c631a","observation_id":"83d39d88-5e49-4bb2-a4b4-21b208896ddd","resolution":{"observed_at":"2026-08-07T12:47:42.785525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:42.547689Z","title":"Sketch me that shoe","venue":null,"work_id":"0a87fa19-f783-4cd0-84c9-3228bb62fd7e","year":2016},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.424719Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:42360ffb9a2ada65bf6e16362c139df24e4f438fd3aa28687c2273179999b809","observation_id":"2ce7b85c-5576-44b2-b9a5-b91488b9bf3b","resolution":{"observed_at":"2026-08-07T12:47:42.605889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:42.372394Z","title":"Paying more at- tention to attention: Improving the performance of convolu- tional neural networks via attention transfer","venue":null,"work_id":"3eaa51fa-5b1a-4be8-83f1-0953e2f84e94","year":2017},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.561384Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:b83a4a88b53261b004c7dd4605ca6afddb53ad990f9d65f4549aa6855f7dcfcc","observation_id":"3e4b7aa7-e633-45da-a79e-65c8b48148ef","resolution":{"observed_at":"2026-08-07T12:47:42.437650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.06160","last_updated":"2018-02-02T01:43:54Z","snapshot_observed_at":"2026-08-14T21:51:59.640867Z","submitted_at":"2016-06-20T15:02:31Z","title":"DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.06160","snapshot_observed_at":"2026-08-07T12:47:41.641751Z","title":"Dorefa-net: Training low bitwidth convo- lutional neural networks with low bitwidth gradients","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.641751Z"},"links":{"cited_paper":"/paper/1606.06160","citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:0e8d20f5e43cbd87cd2343d45e613902a6de2784fed780b7aa39a4bcc9df55b7","observation_id":"85b36368-4a36-49d6-b912-5b8133deb429","resolution":{"observed_at":"2026-08-07T12:47:41.641751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:47:42.182978Z","title":"Dynamic resolution net- work","venue":null,"work_id":"b7339f75-6181-43d0-8346-57125a7a7137","year":2021},"citing_paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:41.728093Z"},"links":{"citing_paper":"/paper/2505.23763"},"observation_digest":"sha256:d1fa5879f9fda423093128bd9e4ccf2cd7ba6069599c40062b75318f7a595631","observation_id":"b138be87-ef15-4ec8-9b44-3da7598b3b06","resolution":{"observed_at":"2026-08-07T12:47:42.294181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.23763","last_updated":"2025-05-29T17:59:51Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T12:42:30.417926Z","submitted_at":"2025-05-29T17:59:51Z","title":"Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch"},"reference_resolution":{"displayed":82,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":0,"verified_fuzzy":69},"total_outbound_references":82},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 0 inbound Pith citation observations for arXiv:2505.23763."}